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Machine Learning Engineer
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We’re looking for a Machine Learning Research Engineer to join an early-stage quantum computing start-up developing full-stack quantum systems.
This role sits at the intersection of advanced ML research and applied engineering, focusing on generative algorithms and hybrid quantum-classical models. You’ll work closely with clients and partners to show how ML and quantum technologies can solve real-world challenges.
Responsibilities:
- Design, implement, and evaluate new machine learning algorithms, particularly generative models (GANs, flow models, diffusion models) and hybrid quantum-classical neural networks.
- Partner with clients to translate practical problems onto the company’s quantum hardware and deliver solutions that demonstrate value.
- Expand and improve the company’s software platform with new algorithms, example applications, and research-driven features.
- Support scientific innovation by publishing findings and helping safeguard intellectual property.
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Required Skills & Experience:
- Proven experience building and testing machine learning algorithms.
- Hands-on experience with GANs, diffusion models, or flow-based generative models.
- Strong programming skills in Python, PyTorch, and version control (Git).
- Advanced degree (Master’s or PhD) in Computer Science, Physics, or a related technical field.
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Preferred Skills:
- Experience working with specialized computing hardware (HPC, NPUs, ASICs, or quantum processors).
- Multi-GPU training experience.
- Publication record in ML or AI research.
- Comfortable presenting and collaborating with clients or stakeholders.
- Familiarity with quantum computing principles.
Why Join:
This role offers the chance to work on cutting-edge ML research applied to quantum hardware, delivering impactful solutions that move from concept to real-world implementation. The position provides hybrid flexibility in London and direct exposure to pioneering quantum technology.
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